Published January 1, 2018
| Version v1
Journal article
Open
Automatic segmentation variability estimation with segmentation priors
Creators
- 1. Hebrew Univ Jerusalem, Rachel & Selim Benin Sch Comp Sci & Engn, Jerusalem, Israel
- 2. Hadassah Hebrew Univ, Med Ctr, Dept Radiol, Jerusalem, Israel
Description
Purpose: Segmentations produced manually by experts or by algorithms are subject to variability, as they depend on many factors, e.g., the structure of interest, the resolution, contrast and quality of the images, and the expert experience or the algorithmic method. To properly assess the quality of these segmentations, it is thus essential to quantify their variability. However, obtaining reference variability ground truth requires several observers to manually delineate structures, which is time-consuming and impractical.
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